Efficient Physical Layer (PHY) network computing in wireless communication technology may rely on efficient resource allocation schemes to improve the flexibility and capacity of the network. Network functions formerly implemented in purpose built hardware are replaced in advanced mobile networks such as, e.g. in 5th generation (5G) networks by software modules operating on shared hardware resources. This imposes a challenge for the operator to maintain the expected quality-of-service (QoS) requirements and/or to avoid that high priority tasks are uncontrollably delayed or eventually dropped.
While previous solutions try to mitigate these problems by identifying worst case scenarios and by dimensioning the amount of hardware resources (e.g. the number of forward error correction (FEC) decoder engines) for the considered worst case scenario, this approach relies on a controversial guess-estimate exercise due to the variety of potential workload corner cases even with low occurrence, and may therefore result costly in over-dimensioning of hardware resources.